Idiap is performing active research on human activity
analysis from multiple sensors. In particular, some
of the conducted works are related to the developement
of behavior recognition in indoor or outdoor scenarios.

As part of our research, we decided to provide some of our
more elaborated code to favor scientific dissemination,
and allow other researchers to test our algorithms,
compare their performance with their own methods,
improve it, or simply use their outcome for further
processing. Of course, we welcome any suggestions or
improvments.

Currently, we are releasing two main algorithms:

a background subtraction algorithm, that
we have shown to provide better performance than the
OpenCV version;

a human detection algorithm dedicated to videos captured by static cameras.
It successfully integrates a joint learning between foreground and
appearance cues.

Further code might be provided in the future (in particular
for multiple object tracking).